Although Detroit battled a slew of injuries to some of their best hitters this season, their offense has performed admirably, with the fifth best wRC+ in baseball. One of the reasons for Detroit’s surprising offensive start is the performance they’ve received from relative unknowns such as Alex Avila, John Hicks, Jim Adduci and Tyler Collins. While some of these performances are unsunstainable, as Avila and Hicks certainly won’t maintain .450+ BABIPs, underlying metrics detect some real improvement in the approach of some of these players.

After watching a handful of Tigers games, it seemed, at least anecdotally, that their hitters were squaring up the ball very well. Surely enough, six of the top 30 hitters (including two of the top three) in Fangraphs’ hard hit percentage metric play for Detroit. Nick Castellanos has always been known as a player who makes hard contact, as have Justin Upton and Miguel Cabrera. But the presence of Alex Avila, second on the list, and Tyler Collins, 23rd, pinged some skepticism. Avila’s 2016 hard-hit percentage with the White Sox was 24 points lower than his 2017 figure, while Tyler Collins posted a 70 wRC+ in AAA last year. Something didn’t make sense.

Detroit averages 10.2% barrels per batted ball overall, with 11.3% at home and a 8.6% mark away. While teams generally hit better at home, I found the contrast to be starker than expected. Could it be possible that Comerica’s Statcast cameras are calibrated differently than other parks, leading to higher recorded exit velocities and launch angles and subsequently more batted ball events being recorded as hard hit and barrels?

Digging deeper into the numbers, I found that that non-Detroit MLB hitters average barreled balls on 6.4% of events. The Tigers average 10.2%, 59% higher than their peers! Strikingly, however, non-Detroit hitters manage a barreled ball on 9.9% of events while playing at Comerica, 55% higher than their non-Comerica average, which lends credence to the theory that something is fishy with Comerica’s Statcast calibration.

Of course, the Tigers could have a pitching staff prone to leaving meatballs over the plate, allowing opposing hitters to outperform their Comerica barrel performance compared to other parks. Diving into Detroit pitcher’s home/away batted ball stats reveals that their hurlers are prone to getting hit hard, with 8.9% of all their non-Comerica batted balls resulting in barrels. That’s compared to MLB hitters averaging 6.3% barrels per event outside of Comerica. Tiger pitchers average a full point higher when at home, giving up 9.9% barrels per batted ball, or 11.2% higher than their away figures. This runs counter to the conventional wisdom of home players retaining an advantage. When looking at all other MLB pitchers, we identify 6.2% barrels per batted ball allowed at home compared to 6.6% away.

That was a lot of numbers and percentages in short order, so let’s recap: the Tigers hitters barrel up the ball at a rate 59% higher than other teams overall. Although Detroit still mashes the ball compared to league average outside Comerica, there is a stark contrast (11.3% to 8.6%) between their barrel performance home and away. Opposition hitters record barrels 55% more at Comerica than away from Comerica. The evidence thus far points to some major issues with Comerica’s Statcast camera calibration.

However, Tiger pitchers have surrendered a lot of barrels, both home and away, decreasing the relevance of opposition hitter performance at Comerica. Yet Detroit pitchers are still 11.2% worse at giving up barrels at Comerica. And when one considers that being at home should provide an advantage to Tigers pitchers, not a disadvantage, some wonkiness with the Comerica Statcast cameras looks increasingly likely.

Conclusions: it seems obvious that there is some systemic issue with how Comerica tracks the speed and launch angle of balls off the bat. With that said, the Tigers hitters do seem generally good at mashing opposing pitches based on their batted ball authority away from home, while their pitchers are prone to leaving gophers over the plate. Given that we are only 30 days into the MLB season, sample size issues could be at play, however batted ball data like this should stabilized fairly quickly given the high number of events tracked. I will revisit this topic in about a month or so to see if the numbers have shifted.